72 citations · 72 across the 2 of their papers we have counts for
6 papers
Multi-Domain Adversarial Feature Generalization for Person Re-Identification
Shan Lin, Chang-Tsun Li, Alex C. Kot
With the assistance of sophisticated training methods applied to single labeled datasets, the performance of fully-supervised person re-identification (Person Re-ID) has been impro…
Multi-frame Feature Aggregation for Real-time Instrument Segmentation in Endoscopic Video
Shan Lin, Fangbo Qin, Haonan Peng +3
Deep learning-based methods have achieved promising results on surgical instrument segmentation. However, the high computation cost may limit the application of deep models to time…
LC-GAN: Image-to-image Translation Based on Generative Adversarial Network for Endoscopic Images
Shan Lin, Fangbo Qin, Yangming Li +3
Intelligent vision is appealing in computer-assisted and robotic surgeries. Vision-based analysis with deep learning usually requires large labeled datasets, but manual data labeli…
Towards Better Surgical Instrument Segmentation in Endoscopic Vision: Multi-Angle Feature Aggregation and Contour Supervision
Fangbo Qin, Shan Lin, Yangming Li +3
Accurate and real-time surgical instrument segmentation is important in the endoscopic vision of robot-assisted surgery, and significant challenges are posed by frequent instrument…
Homogeneous Feature Transfer and Heterogeneous Location Fine-tuning for Cross-City Property Appraisal Framework
Yihan Guo, Shan Lin, Xiao Ma +2
Most existing real estate appraisal methods focus on building accuracy and reliable models from a given dataset but pay little attention to the extensibility of their trained model…
Multi-task Mid-level Feature Alignment Network for Unsupervised Cross-Dataset Person Re-Identification
Shan Lin, Haoliang Li, Chang-Tsun Li +1
Most existing person re-identification (Re-ID) approaches follow a supervised learning framework, in which a large number of labelled matching pairs are required for training. Such…